CN115291216B - Satellite-borne SAR image acquisition method and device, electronic equipment and medium - Google Patents
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Abstract
The invention provides a method and a device for acquiring a satellite-borne SAR image, electronic equipment and a medium, and relates to the technical field of synthetic aperture radars. The specific implementation mode comprises the following steps: acquiring satellite-borne SAR echo data for a target region, the target region comprising N target A target sub-region; aiming at each target subregion, determining a first target subregion track mapping relation corresponding to the target subregion according to the satellite-borne SAR echo data and the satellite track model respectively; determining a plurality of first target area track mapping relations corresponding to the target areas according to the satellite-borne SAR echo data and the satellite track model; according to N target Determining a second target area track mapping relation corresponding to the target area according to the first target subarea track mapping relation and the first target area track mapping relation; and determining a satellite-borne SAR image aiming at the target area according to the second target area track mapping relation and the satellite-borne SAR echo data aiming at the target area.
Description
Technical Field
The present invention relates to the field of synthetic aperture radar technology, and in particular, to a method and an apparatus for acquiring a satellite-borne SAR image, an electronic device, a storage medium, and a computer program product.
Background
In the field of satellite-borne Synthetic Aperture Radar (SAR) imaging technology, satellite trajectory errors are one of the main factors affecting the quality of a satellite-borne SAR image.
Satellite trajectory errors are primarily the deviations between the measured and actual values of the satellite platform position, which can cause errors in the instantaneous slope distance. The instantaneous slope is an important parameter for constructing the azimuth matched filter, so the deviation of the instantaneous slope can cause the azimuth matched filter to be mismatched, and the resolution loss, the signal-to-noise ratio reduction and the like are caused. In addition, the instantaneous slope distance is also related to the position calculation of the target, and the error of the instantaneous slope distance also influences the positioning accuracy of the target. Therefore, when the satellite-borne SAR trajectory error is large, the problem of defocusing the SAR image usually occurs, thereby reducing the quality of the SAR image.
Disclosure of Invention
The invention provides a method and a device for acquiring a satellite-borne SAR image, electronic equipment, a storage medium and a computer program product, which aim to at least partially solve the technical problems.
According to one aspect of the invention, a method for acquiring a satellite-borne SAR image is provided, which comprises the following steps: acquiring satellite-borne SAR echo data for a target region, wherein the target region comprises N target A target sub-region, N target Is an integer of 3 or more; for N target Each target sub-area in each target sub-area is determined within the imaging time of the target sub-area according to the satellite-borne SAR echo data 1 The track points of the satellite corresponding to each azimuth moment are determined according to N 1 Determining a first target sub-region track mapping relation corresponding to the target sub-region by using the individual track points and the satellite track model, N 1 Is an integer of 3 or more; determining N within the imaging time of the target region according to the satellite-borne SAR echo data 2 Orbit of satellite corresponding to each azimuth momentIs counted and is according to N 2 A plurality of track points and a satellite track model, determining a plurality of first target area track mapping relations corresponding to the target area, N 2 Is an integer of 5 or more; according to N target Determining a second target area track mapping relation corresponding to the target area according to the first target subarea track mapping relation and the first target area track mapping relation; and determining the satellite-borne SAR image aiming at the target area according to the second target area track mapping relation and the satellite-borne SAR echo data aiming at the target area.
According to an embodiment of the invention, according to N 1 Determining a first target sub-region track mapping relation corresponding to the target sub-region by the track points and the satellite track model comprises the following steps: for N 1 Each track point in the track points determines a plurality of first reference track points associated with the track point according to the track point and the first step length; according to N 1 A track point and N 1 The plurality of track points are respectively associated with a plurality of first reference track points to obtain a plurality of first track point combinations; determining a plurality of second target sub-area track mapping relations corresponding to the target sub-areas according to the plurality of first track point combinations and the satellite track model; and determining a target sub-region track optimization mapping relation from the plurality of second target sub-region track mapping relations as a first target sub-region track mapping relation.
According to an embodiment of the invention, according to N 1 Determining a first target sub-region track mapping relation corresponding to the target sub-region by the track points and the satellite track model further comprises: in response to the target sub-region track optimization mapping relation not being matched from the plurality of second target sub-region track mapping relations, updating the first step size to be a second step size; and based on the second step size, repeatedly executing the operation of determining the target sub-region track optimization mapping relation from the plurality of second target sub-region track mapping relations as the first target sub-region track mapping relation.
According to an embodiment of the present invention, determining the target sub-region trajectory optimization mapping relationship from the plurality of second target sub-region trajectory mapping relationships comprises: imaging the target sub-region by using the plurality of second target sub-region track mapping relations and the satellite-borne SAR echo data corresponding to the target sub-region respectively to obtain a plurality of complex image data; obtaining a plurality of imaging contrasts according to the plurality of complex image data; and responding to the trigger of a preset condition, and taking a second target subregion track mapping relation corresponding to the maximum imaging contrast in the multiple imaging contrasts as a target subregion track optimization mapping relation.
According to an embodiment of the invention, the preset condition comprises at least one of: the increment of the maximum imaging contrast obtained by the optimization at this time relative to the maximum imaging contrast obtained by the previous optimization is less than or equal to a first threshold; and the step length corresponding to the optimization is less than or equal to a second threshold value.
According to an embodiment of the present invention, N target The first target sub-area track mapping relationship and the first target area track mapping relationship are determined, and the determining of the second target area track mapping relationship corresponding to the target area comprises: for N target Each of the first target sub-region track mapping relations is determined with N within the imaging time of the target sub-region orb The track points of the satellite corresponding to the azimuth moments are determined respectively by N based on the track mapping relation of the first target sub-area orb The slant distance between each track point and the central target point of the target sub-area is obtained to obtain N orb A first pitch; n is a radical of hydrogen orb Is an integer of 3 or more; for each of a plurality of first target area trajectory mapping relationships, determining N based on the first target area trajectory mapping relationship target N corresponding to each target sub-region in each target sub-region orb The slope distance at each azimuth moment is obtained as N target *N orb A plurality of second slope distances, determining N for each of the plurality of first target area trajectory mapping relationships target *N orb A second slope distance and N target N of the first target sub-region track mapping relation orb A degree of deviation between the first slope distances; and determining a target area track optimization mapping relation from the plurality of first target area track mapping relations as a second target area track based on the deviation degreeAnd (5) mapping relation.
According to an embodiment of the invention, according to N 2 Determining a plurality of first target area track mapping relationships corresponding to the target area by using the track points and the satellite track model comprises: for N 2 Determining a plurality of second reference track points associated with each track point according to the track point and the third step length; according to N 2 A track point and N 2 The plurality of track points are respectively associated with a plurality of second reference track points to obtain a plurality of second track point combinations; and determining a plurality of first target area track mapping relations corresponding to the target areas according to the plurality of second track point combinations and the satellite track model.
According to an embodiment of the present invention, N target Determining a second target area track mapping relation corresponding to the target area further comprises: updating the third step size to a fourth step size in response to not matching the target area track optimization mapping relationship from the plurality of first target area track mapping relationships based on the degree of deviation; and based on the fourth step size, repeatedly executing the operation of determining the target area track optimization mapping relation from the plurality of first target area track mapping relations as the second target area track mapping relation.
According to an embodiment of the present invention, determining, as the second target area trajectory mapping relationship, a target area trajectory optimization mapping relationship from the plurality of first target area trajectory mapping relationships based on the degree of deviation includes: determining a minimum degree of deviation from a plurality of degrees of deviation; and determining the first target area track mapping relation corresponding to the minimum deviation degree as a target area track optimization mapping relation in response to the minimum deviation degree being smaller than or equal to a third threshold value.
According to an embodiment of the present invention, determining, as the second target area trajectory mapping relationship, a target area trajectory optimization mapping relationship from the plurality of first target area trajectory mapping relationships based on the degree of deviation includes: determining a minimum degree of deviation from a plurality of degrees of deviation; and determining the first target area track mapping relation corresponding to the minimum deviation degree as the target area track optimization mapping relation in response to the step length corresponding to the optimization is smaller than or equal to the fourth threshold.
According to another aspect of the present invention, there is provided a satellite-borne SAR image acquisition apparatus, comprising: an acquisition module for acquiring satellite-borne SAR echo data for a target region, wherein the target region comprises N target A target sub-region, N target Is an integer of 3 or more; a first mapping module for mapping N target Each target sub-area in the target sub-areas is determined and N is determined within the imaging time of the target sub-area according to the satellite-borne SAR echo data 1 The track points of the satellite corresponding to each azimuth moment are determined according to N 1 Determining a first target sub-region track mapping relation corresponding to the target sub-region by using the individual track points and the satellite track model, N 1 Is an integer of 3 or more; a second mapping module for determining N in the imaging time of the target region according to the satellite-borne SAR echo data 2 The track points of the satellite corresponding to each azimuth moment are determined according to N 2 Determining a plurality of first target area track mapping relations corresponding to the target areas by using the track points and the satellite track model, N 2 Is an integer of 5 or more; a determination module for determining according to N target Determining a second target area track mapping relation corresponding to the target area according to the first target subarea track mapping relation and the first target area track mapping relation; and the imaging module is used for determining a satellite-borne SAR image aiming at the target area according to the second target area track mapping relation and the satellite-borne SAR echo data aiming at the target area.
According to another aspect of the present invention, there is provided an electronic apparatus including: one or more processors; memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform operations that implement the methods described above.
According to another aspect of the present invention, there is provided a computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform a method implementing the above.
According to another aspect of the invention, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method as described above.
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To further illustrate the technical content of the present invention, the following detailed description is given with reference to the examples and the accompanying drawings, in which:
fig. 1 is a flowchart of a method for acquiring a space-borne SAR image according to an embodiment of the present invention;
fig. 2 is a schematic illustration of a method of determining a plurality of first reference track points associated with each track point, in accordance with an embodiment of the invention;
FIG. 3 is an imaging model during determination of a target sub-region trajectory optimization mapping relationship according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a method for finding a target sub-region trajectory optimization mapping relationship according to an embodiment of the present invention;
FIG. 5 is a flowchart of a method of determining a second target area trajectory mapping relationship in accordance with an embodiment of the present invention;
FIGS. 6A and 6B are simulation experiment results before the method of the present invention is used to improve the image quality of the target sub-region;
fig. 7 and fig. 8A to 8D are respectively simulation experiment results of performing improvement processing on the quality of a point target imaging image by using the method of the present invention;
FIG. 9 is the result of imaging a point object within a target area prior to processing using the method of the present invention;
fig. 10A to 10E are results of image quality improvement of each point target by the optimal trajectory estimation of the target area;
fig. 11 is a block diagram of a spaceborne SAR image acquisition device according to an embodiment of the present invention; and
fig. 12 is a block diagram of an electronic device for implementing the method for acquiring a SAR image according to an embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments and the drawings in the embodiments. It should be apparent that the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the sequence numbers of the operations in the following methods are only used as a representation of the operations for description, and should not be regarded as representing the execution sequence of the operations. The method need not be performed in the exact order shown, unless explicitly stated.
Fig. 1 is a flowchart of a method for acquiring a space-borne SAR image according to an embodiment of the present invention.
As shown in FIG. 1, the method for acquiring the satellite-borne SAR image comprises operations S110-S150.
In operation S110, on-board SAR echo data for a target region is acquired, wherein the target region includes N target A target sub-region.
In operation S120, for N target Each target sub-area in each target sub-area is determined within the imaging time of the target sub-area according to the satellite-borne SAR echo data 1 The track points of the satellite corresponding to each azimuth moment are determined according to N 1 And determining a first target sub-area track mapping relation corresponding to the target sub-area by the track points and the satellite track model.
In operation S130, N is determined within an imaging time of a target region from satellite-borne SAR echo data 2 The track points of the satellite corresponding to each azimuth moment are determined according to N 2 And determining a plurality of first target area track mapping relations corresponding to the target areas by the track points and the satellite track model.
In operation S140, according to N target And determining a second target area track mapping relation corresponding to the target area according to the first target sub-area track mapping relation and the plurality of first target area track mapping relations.
In operation S150, a satellite-borne SAR image for the target region is determined according to the second target region trajectory mapping relationship and the satellite-borne SAR echo data for the target region.
According to an embodiment of the invention, the target area may for example comprise N target A target sub-region, N target Is an integer of 3 or more. The on-board SAR echo data for the target region comprises for N target Satellite-borne SAR echo data for each target sub-region. The satellite-borne SAR echo data for each target sub-region can be used for imaging processing of the target sub-region, and the satellite-borne SAR echo data for each target region can be used for imaging processing of the target region.
According to the embodiment of the invention, because the motion track of the satellite-borne SAR satellite is a smooth curve, according to the characteristic, the track process of the satellite in the imaging time of the target area (or the target sub-area) can be described by using a satellite track model. Considering that the satellite-borne SAR track error has the characteristic of low-order error, the polynomial coefficient in the satellite track model can be used for correcting the motion track error of the satellite, so that the imaging quality of the satellite-borne SAR echo data is improved.
Since the motion trajectory of the satellite-borne SAR satellite is a smooth curve, the motion trajectory of the satellite in the imaging time of the target area (or the target sub-area) can be regarded as being composed of a series of track points, and each track point is used for representing the instantaneous position of the satellite at the corresponding azimuth moment. Subsequently, a plurality of track points can be selected from the track points to fit to obtain a polynomial coefficient of the optimal satellite track model, the polynomial coefficient is applied to the satellite track model to obtain a track mapping relation of the target area (or the target sub-area), and then the track mapping relation of the target area (or the target sub-area) is used for imaging processing to obtain a satellite-borne SAR image aiming at the target area (or the target sub-area). The polynomial coefficient of the optimal satellite trajectory model means that the satellite trajectory model obtained based on the polynomial coefficient has the smallest trajectory error when a certain condition is satisfied.
Based on the above mechanism, for eachA target sub-region for which N can be determined from the satellite-borne echo data 1 Track point, N, of satellite corresponding to each azimuth time 1 Is an integer of 3 or more. Next, can be based on N 1 And determining a first target sub-area track mapping relation corresponding to the target sub-area by the track points and the satellite track model. Wherein the first target sub-region trajectory mapping relationship is an optimal trajectory estimate for the target sub-region that describes a trajectory history of the satellite with a minimum satellite trajectory error over an imaging time of the target sub-region. And correcting the imaging error of the target sub-region by utilizing the first target sub-region track mapping relation.
According to the embodiment of the invention, for a target area, N is determined from satellite-borne SAR echo data of the target area in the imaging time of the target area 2 Track point, N, of satellite corresponding to each azimuth moment 2 Is an integer of 5 or more. Then according to N 2 And determining a plurality of first target area track mapping relations corresponding to the target areas by the track points and the satellite track model. Wherein the first target region trajectory map is a potentially optimal trajectory estimate for the target region that describes a trajectory history of the satellite potentially with a minimum satellite trajectory error over an imaging time of the target region.
It can be appreciated that the first target sub-region trajectory mapping relationship is an optimal trajectory estimate for the target sub-region, which in effect represents the ramp distance history that is closest to the real world in the target sub-region imaging time. At the acquisition of N target After the first target sub-region trajectory mapping relationships and the first target region trajectory mapping relationships, N may be utilized target The first target sub-region trajectory mapping relationships determine a second target region trajectory mapping relationship corresponding to the target region from the plurality of first target region trajectory mapping relationships. Wherein the second target region trajectory map is an optimal trajectory estimate for the target region that describes a trajectory history of the satellite with a minimum satellite trajectory error over an imaging time of the target region. By using the second eyeThe target area trajectory mapping relation can correct imaging errors of the target area, and therefore quality improvement of the satellite-borne SAR image aiming at the target area is achieved.
Next, imaging processing may be performed according to the second target region trajectory mapping relationship and the satellite-borne SAR echo data for the target region, thereby determining a satellite-borne SAR image for the target region. It is to be understood that, in the embodiment of the present invention, any one or more suitable manners may be adopted to perform the satellite-borne SAR imaging processing (including performing imaging processing on the target region and the target sub-region), which may be specifically selected according to actual needs, and the present invention is not limited thereto.
In the scheme of the embodiment of the invention, based on the characteristic of satellite orbit smoothness, the first target sub-area track mapping relations corresponding to a plurality of target sub-areas are respectively determined by utilizing a satellite orbit model and a plurality of track points, and the second target area track mapping relation corresponding to the target area is determined from the first target area track mapping relations based on the first target sub-area track mapping relations, so that the optimal track estimation for a local area and an overall area is obtained, the accurate estimation and compensation of the slant-range error in the corresponding imaging time of the area can be ensured, and the quality of the satellite-borne SAR image is improved.
According to an embodiment of the present invention, in the above operation S120, according to N 1 Determining a first target sub-region trajectory mapping relationship corresponding to the target sub-region may include the following operations.
For N 1 Determining a plurality of first reference track points associated with each track point according to the track point and the first step length; according to N 1 A track point and N 1 The plurality of track points are respectively associated with a plurality of first reference track points to obtain a plurality of first track point combinations; determining a plurality of second target sub-area track mapping relations corresponding to the target sub-areas according to the plurality of first track point combinations and the satellite track model; and determining a target sub-region track optimization mapping relation from the plurality of second target sub-region track mapping relations as a first targetAnd mapping relation of the target area track.
Fig. 2 is a schematic diagram of a method of determining a plurality of first reference track points associated with each track point, according to an embodiment of the invention. An example process of determining a plurality of first reference track points associated with the track point P will be described below taking the track point P as an example.
As shown in fig. 2, in the three-dimensional spatial coordinate system xyz, the y direction represents the azimuth direction of the satellite trajectory, i.e., the track direction. The (x-z) plane represents the plane perpendicular to the track direction.
For example, for a track point P, its corresponding coordinates on the (x-z) plane are (x, z). With the track point P as the center and the first step length η as the step length, a grid as shown in fig. 2 is established and evaluated, and a plurality of first reference track points associated with the track point P, such as a first reference track point P1, a first reference track point P2, a first reference track point P3, and a first reference track point P4, can be obtained. The coordinates of the first reference trace points P1 to P4 on the (x-z) plane are (x, z + η), (x + η, z), (x, z- η), (x- η, z), respectively.
Similarly for N 1 Any other one of the plurality of trace points may be used to determine the plurality of first reference trace points associated with the trace points using the method described above. Subsequent N 1 The plurality of track points and the corresponding first reference track points thereof can be used to form a plurality of first track point combinations.
According to an embodiment of the invention, the first combination of trace points is composed of N 1 And the track point set is formed by the track points corresponding to the azimuth moments or the first reference track points. The number of first track point combinations is determined by the number of track points and the number of first reference track points associated with a track point.
For example, assume N 1 The track points corresponding to the azimuth moments comprise track points P, G and M, wherein a plurality of first reference track points associated with each track point are 4, and the number of first track point combinations is 5 3 . In one example, the first combination of trace points can be represented as (P, G, M), (P, G1, M1), or (P2, G, M1), for example, and so on, whereP2, G1 and M1 are respectively a first reference track point of track point P, track point G and track point M.
According to the embodiment of the invention, a polynomial coefficient of a group of satellite trajectory models can be obtained through fitting according to the first track point combination, and the polynomial coefficient is applied to the satellite trajectory models, so that a second target sub-region trajectory mapping relation corresponding to the target sub-region can be obtained. The first track point combination and the second target sub-area track mapping relation have a one-to-one correspondence relation.
In one example, the satellite trajectory model may be represented using the following equation (1).
In the formula (1), (X) s , Y s , Z s ) Representing the instantaneous position of the satellite, N-1 the order of the polynomial of the satellite trajectory model, t the azimuth sampling instant, (a) n ,b n ,c n ) (N =0, \8230;, N-1) represents polynomial coefficients in the satellite trajectory model. Wherein N can be determined according to the number of trace points in the first trace point combination.
According to the first track point combination and the satellite track model shown in the formula (1), an expression of polynomial coefficients of the satellite track model can be obtained through solving. It should be noted that the polynomial coefficient a n 、b n And c n Similarly, in order to save space, the polynomial coefficient a is solved n The solving process of the polynomial coefficients is illustrated.
In the embodiment of the present invention, the polynomial coefficient a of the satellite trajectory model shown in equation (2) may be obtained by solving according to the first combination of trajectory points and the satellite trajectory model shown in equation (1) n The expression (c).
In the formulas (2) to (5),a matrix representation representing the components of the polynomial coefficients in the x-direction, a representing a matrix of coefficients of size N x N generated from the selected azimuth instants, L a Representing the component of the instantaneous position of the satellite in the x-direction at N azimuth times, T representing the matrix transposition, T i (i =1, \8230;, N) denotes the ith azimuth sampling time, X Si (i =1, \8230;, N) represents the position coordinates in the x direction of the instantaneous position of the satellite at the instant of the ith bearing, a n (N =0, \8230;, N-1) represents polynomial order coefficients of the position coordinates of the satellite in the x direction as a function of the azimuth time.
Similarly, one can rely on the polynomial coefficient a n To obtain a polynomial coefficient b n And c n Polynomial coefficient b n And c n Respectively with polynomial coefficient a n Have similar expression forms and are not described in detail here.
Next, a polynomial coefficient a is obtained n 、b n And c n Thereafter, the polynomial coefficient a may be scaled n 、b n And c n Application toAnd (3) obtaining a second target sub-area track mapping relation corresponding to the target sub-area by the formula (1). Similarly, by adopting the method described above, according to the plurality of first track point combinations and the satellite trajectory model, a plurality of second target sub-region trajectory mapping relations corresponding to the target sub-region can be determined.
According to an embodiment of the present invention, determining the target sub-region trajectory optimization mapping relationship from the plurality of second target sub-region trajectory mapping relationships may include the following operations.
Imaging the target sub-region by using the plurality of second target sub-region track mapping relations and the satellite-borne SAR echo data corresponding to the target sub-region respectively to obtain a plurality of complex image data; obtaining a plurality of imaging contrasts according to the plurality of complex image data; and responding to the trigger of a preset condition, and taking a second target sub-region track mapping relation corresponding to the maximum imaging contrast in the multiple imaging contrasts as a target sub-region track optimization mapping relation.
According to the embodiment of the invention, different first track point combinations can be fitted to obtain the corresponding second target sub-region track mapping relations. Each second target sub-region trajectory mapping relationship is a preliminary trajectory estimate for the target sub-region that describes a trajectory history of the satellite for an imaging time of the target sub-region that potentially has a minimum satellite trajectory error. The individual trajectory histories may produce different ramp histories for the same target sub-region, thereby producing different instantaneous ramp errors, which ultimately appear as differences in imaging quality.
In order to reduce the satellite trajectory error in the imaging process for the target sub-region, so as to minimize the slant range error in the imaging process for the target sub-region, and thus optimize the focusing effect of the imaging result, the target sub-region trajectory optimization mapping relationship may be determined from a plurality of second target sub-region trajectory mapping relationships based on a criterion of maximum contrast, and the target sub-region trajectory optimization mapping relationship is used as the first target sub-region trajectory mapping relationship.
According to the embodiment of the invention, a plurality of complex image data can be obtained by respectively utilizing the track mapping relations of the second target sub-regions and the satellite-borne SAR echo data corresponding to the target sub-regions to perform imaging processing on the target sub-regions. From the plurality of complex image data, a plurality of imaging contrasts can be obtained.
In one example, the imaging contrast may be determined using the following equation (6).
In the formula (6), the first and second groups,the contrast of the image is represented by,representing the variance of the amplitude of the complex image,represents the mean value of the amplitude of the complex image,representing complex image data.
According to an embodiment of the invention, the variance of the complex image amplitude and the mean of the complex image amplitude may be determined from the complex image data. In one example, the variance of the complex image amplitude and the mean of the complex image amplitude may be determined using equation (7) and equation (8) below, respectively.
In formula (7) and formula (8), k denotes a distance-direction sampling time, t denotes an azimuth-direction sampling time, and M denotes a pixel size of the complex image.
Based on the above equations (6) to (8), a plurality of imaging contrasts corresponding to the plurality of complex image data can be obtained from the plurality of complex image data. Under the condition that the preset condition is met, a second target sub-region track mapping relation corresponding to the maximum imaging contrast can be determined from the multiple imaging contrasts on the basis of the criterion of the maximum contrast, and the second target sub-region track mapping relation is used as a target sub-region track optimization mapping relation.
In some embodiments, if the preset condition is not satisfied, the target sub-region trajectory optimization mapping relationship cannot be matched from the plurality of second target sub-region trajectory mapping relationships, that is, the optimal target sub-region trajectory mapping relationship corresponding to the target sub-region cannot be found. In this case, the first step size may be updated to a second step size, and the operation of determining the target sub-region track optimization mapping relation from the plurality of second target sub-region track mapping relations as the first target sub-region track mapping relation is repeatedly performed based on the second step size. And if the target sub-region track optimization mapping relation can be determined from the plurality of second target sub-region track mapping relations based on the second step length, taking the target sub-region track optimization mapping relation as the first target sub-region track mapping relation. It should be noted that the process of determining the target sub-region track optimized mapping relationship from the plurality of second target sub-region track mapping relationships as the first target sub-region track mapping relationship based on the second step length is similar to the process of determining the target sub-region track optimized mapping relationship from the plurality of second target sub-region track mapping relationships as the first target sub-region track mapping relationship based on the first step length, and details are not repeated here.
According to an embodiment of the present invention, a plurality of second steps may be set for performing a plurality of rounds of optimization. For example, in the case that the mapping relationship is not optimized by using one second step size to the target sub-region track, the optimization can be performed by using another second step size; and repeating the operation until a target sub-region track optimization mapping relation is determined to be used as the first target sub-region track mapping relation, or the target sub-region track optimization mapping relation does not exist.
According to an embodiment of the present invention, the preset condition described above includes at least one of: the increment of the maximum imaging contrast obtained by the optimization for the maximum imaging contrast obtained by the previous optimization is smaller than or equal to a first threshold, and the step length corresponding to the optimization is smaller than or equal to a second threshold. It is to be understood that the first threshold and the second threshold, and the first step size and the second step size may be set according to practical situations, and the present invention is not limited thereto.
An example process for finding the optimal mapping relationship of the target sub-region trajectory will be described below with reference to fig. 3 and 4.
FIG. 3 is an imaging model in a process of determining a target sub-region trajectory optimization mapping relationship according to an embodiment of the invention.
As shown in fig. 3, the y direction represents the azimuth direction of the satellite trajectory, i.e., the track direction. The (x-z) plane represents the plane perpendicular to the track direction. Point Q represents the central target point of the target sub-area. The satellite flies in the y direction and an actual trajectory of the satellite's flight can be determined (as shown by the dashed line in fig. 3). A plurality of trajectory points are determined from the actual trajectory within the imaging time range of the target sub-region. An ideal trajectory (shown as a solid line in fig. 3) can be fitted from the plurality of trace points.
In FIG. 3, R e 、R s Respectively representing the slope distance with the error at the center target point Q and the actual slope distance. By comparing R e And R s It can be known that the error of the instantaneous slope distance can be caused by the existence of the satellite track error. And the error of the instantaneous slope distance can influence the positioning precision of the target, thereby reducing the quality of the SAR image.
As described above, the motion trajectory of the satellite-borne SAR satellite can be regarded as a smooth curve. Based on this feature, the satellite orbit position can be described by using a satellite orbit model. In addition, considering that the satellite-borne SAR track error has the characteristic of low-order error, the polynomial coefficient in the satellite track model can be used for correcting the motion track error of the satellite, so that the imaging quality of the satellite-borne SAR echo data is improved. Thus, the trajectory history problem for solving the minimum satellite trajectory error can be converted to a polynomial coefficient for finding an optimal set of satellite trajectory models. However, the order of the coefficients of the polynomial in the satellite trajectory model is very different, and the linear term and the constant term cannot be searched, so that the polynomial coefficients cannot be directly searched and optimized. In the embodiment of the invention, a method for searching the position of the iteration track point can be adopted to optimize the polynomial coefficient so as to obtain the target sub-region track optimization mapping relation, and further the imaging quality of the satellite-borne SAR echo data is improved by utilizing the target sub-region track optimization mapping relation.
FIG. 4 is a schematic diagram of a method for finding a target sub-region trajectory optimization mapping relationship according to an embodiment of the present invention.
As shown in FIG. 4, the method for finding the optimal mapping relationship of the target sub-region track includes operations S401 to S409.
In operation S401, N is acquired 1 And (5) tracing points. According to the embodiment of the invention, N is determined from satellite-borne SAR echo data in the imaging time of the target subregion 1 Track point, N, of satellite corresponding to each azimuth time 1 Is an integer of 3 or more to obtain N 1 And (5) tracing points.
In operation S402, a first step size is acquired. According to an embodiment of the present invention, the first step length may be set according to actual conditions, which is not limited by the present invention.
In operation S403, a plurality of first track point combinations is determined.
According to an embodiment of the present invention, for N 1 Each of the plurality of trace points may determine a plurality of first reference trace points associated with the trace point according to the trace point and the first step size, and determine a plurality of second reference trace points associated with the trace point according to N 1 A track point and N 1 And obtaining a plurality of first track point combinations by a plurality of first reference track points which are respectively associated with the plurality of track points. The manner of determining the combination of the first reference trace point and the first trace point is similar to the above-described process, and is not described herein again.
In operation S404, a plurality of second target sub-region trajectory mapping relationships are determined. According to the embodiment of the invention, based on the formulas (1) - (5), a plurality of second target sub-region track mapping relations can be obtained through fitting according to the combination of the plurality of first track points.
In operation S405, a plurality of complex image data is determined.
For example, a plurality of complex image data can be obtained by performing imaging processing on the target sub-region by using a plurality of second target sub-region trajectory mapping relationships and satellite-borne SAR echo data corresponding to the target sub-region.
In operation S406, a plurality of imaging contrasts is determined. According to the embodiments of the present invention, based on the above formulas (6) to (8), a plurality of imaging contrasts can be determined from a plurality of complex image data.
In operation S407, it is determined whether a preset condition is satisfied, if yes, operation S408 is performed, otherwise, operation S409 is performed.
The preset condition may include at least one of: and determining that the increment of the maximum imaging contrast obtained by the optimization is less than or equal to a first threshold relative to the maximum imaging contrast obtained by the previous optimization, and the step length corresponding to the optimization is less than or equal to a second threshold. If the preset condition is satisfied, operation S408 is performed, otherwise, operation S409 is performed.
In operation S408, a second target sub-region trajectory mapping relationship corresponding to a maximum imaging contrast of the multiple imaging contrasts is used as a target sub-region trajectory optimization mapping relationship.
In operation S409, the first step size is updated to be the second step size, and operations S403 to S407 are repeatedly performed until the target sub-region track optimization mapping relationship is determined.
According to the embodiment of the invention, if the preset condition is not met, the situation that the matched target sub-area track optimization mapping relation is not found is shown. At this time, the first step size may be updated to a second step size, and operations S403 to 407 are repeatedly performed until the target sub-region trajectory optimization mapping relationship is determined. Then, the target sub-region track optimization mapping relation is used as a first target sub-region track mapping relation, so that the imaging of the satellite-borne SAR echo data of the target sub-region can be corrected by utilizing the first target sub-region track mapping relation in the following process, and the quality of the satellite-borne SAR image in the imaging time range of the target sub-region is improved.
According to an embodiment of the present invention, in the above operation S130, according to N 2 The method comprises the following steps of determining a plurality of first target area track mapping relations corresponding to target areas by using track points and a satellite track model.
For N 2 Determining a plurality of second reference track points associated with each track point according to the track point and the third step length; according to N 2 A track point and N 2 The plurality of track points are respectively associated with a plurality of second reference track points to obtain a plurality of second track point combinations; and determining a plurality of first target area track mapping relations corresponding to the target areas according to the plurality of second track point combinations and the satellite track model.
In the embodiment of the present invention, the process of determining the second reference track point, the second track point combination, and the plurality of first target area track mapping relationships is the same as or similar to the process of determining the first reference track point, the first track point combination, and the plurality of second target sub-area track mapping relationships, and is not repeated here for saving space.
According to an embodiment of the invention, the first target sub-region trajectory mapping relationship is an optimal trajectory estimation for the target sub-region, which in practice represents a slope history closest to the real situation within the target sub-region imaging time. However, the sensitivity to satellite trajectory errors varies from imaging geometry to imaging geometry over the imaging time frame for the target region. In order to obtain the optimal trajectory estimation aiming at the target area and realize the quality improvement of the satellite-borne SAR image aiming at the target area, the method can be used for obtaining the optimal trajectory estimation aiming at the target area target After the track mapping relation of the first target sub-area corresponding to each target sub-area is utilized, N is utilized target The first target sub-region trajectory mapping relationship determines a second target region trajectory mapping relationship for the target region to utilize the second target region trajectory mapping relationship to improve image quality over a target region imaging time range.
FIG. 5 is a flowchart of a method of determining a second target area trajectory mapping relationship in accordance with an embodiment of the present invention.
As shown in FIG. 5, the method for determining the second target area track mapping relationship includes operations S541-S544.
In operation S541, for N target Each of the first target sub-region track mapping relations is determined with N within the imaging time of the target sub-region orb The track points of the satellite corresponding to the azimuth time are determined respectively based on the track mapping relation of the first target sub-area orb The slant distance between each track point and the central target point of the target sub-area is obtained to obtain N orb A first slope distance.
In operation S542, for each of a plurality of first target area track mappings, N is determined based on the first target area track mapping target N corresponding to each target sub-region in the target sub-regions orb The slope distance at each azimuth moment is obtained as N target *N orb A second slope distance.
In operation S543, N is determined for each of a plurality of first target region trajectory mapping relationships target *N orb A second slope distance and N target N of the first target sub-region track mapping relation orb The degree of deviation between the first slope distances.
In operation S544, a target region trajectory optimization mapping relationship is determined from the plurality of first target region trajectory mapping relationships as a second target region trajectory mapping relationship based on the degree of deviation.
According to an embodiment of the present invention, the target area comprises N target A target sub-region, N target Each of the target sub-regions respectively corresponds to a first target sub-region track mapping relationship. For each first target sub-region trajectory mapping relation, determining N in the imaging time of the target sub-region orb Track point, N, of satellite corresponding to each azimuth time orb Is an integer of 3 or more. Then, respectively determining N based on the first target sub-region track mapping relation orb Skew between a trajectory point and a central target point of the target sub-areaFrom a distance of N to orb A first slope distance. By the above method, based on N target The mapping relation of the first target sub-area track can obtain N target *N orb A first slope distance.
According to an embodiment of the present invention, for each first target area trajectory mapping relationship, N may be determined from the first target area trajectory mapping relationship target N corresponding to each target sub-region in the target sub-regions orb The slope distance at each azimuth moment is obtained as N target *N orb A second slope distance.
It will be appreciated that the first target region trajectory mapping relationship is a potentially optimal trajectory estimate for the target region that describes the trajectory histories of the satellites potentially with minimal satellite trajectory errors over the imaging time of the target region. And the first target sub-region trajectory mapping relationship is an optimal trajectory estimate for the target sub-region. If the integral track and N within the target area imaging time are represented by the first target area track mapping relation target The local tracks of the targets in the target sub-region imaging time represented by the first target sub-region track mapping relation can be well attached, so that the deviation between the slope distance process of the targets in each target sub-region under the integral track estimation and the slope distance process under the optimal track estimation of the target sub-region is as small as possible, and the first target region track mapping relation is relatively large and is possibly the optimal track estimation aiming at the target region.
Based on this mechanism, it can be based on N target N obtained by mapping relation of first target sub-area tracks target *N orb The first slope distance and N obtained based on the first target area track mapping relation target *N orb And determining a target area track optimization mapping relation from the plurality of first target area track mapping relations as a second target area track mapping relation according to the deviation degree between the second slope distances.
It will be appreciated that a degree of deviation may be determined based on each first target area trajectory mapping relationship. Therefore, a plurality of degrees of deviation can be determined from a plurality of first target area trajectory mappings.
According to an embodiment of the present invention, determining a target area trajectory optimization mapping relationship from a plurality of first target area trajectory mapping relationships as a second target area trajectory mapping relationship based on the degree of deviation may include the following operations: and under the condition that the minimum deviation degree is less than or equal to a third threshold value, determining a first target area track mapping relation corresponding to the minimum deviation degree as a target area track optimization mapping relation. Therefore, the target area track optimization mapping relation is determined from the plurality of first target area track mapping relations to serve as the second target area track mapping relation.
In some embodiments, determining the target area trajectory optimization mapping from the plurality of first target area trajectory mapping relationships as the second target area trajectory mapping relationship based on the degree of deviation may further include: and determining the minimum deviation degree from the multiple deviation degrees, and determining the first target area track mapping relation corresponding to the minimum deviation degree as the target area track optimization mapping relation under the condition that the step length corresponding to the optimization is less than or equal to the fourth threshold value. Therefore, the target area track optimization mapping relation is determined from the plurality of first target area track mapping relations to serve as the second target area track mapping relation.
According to the embodiment of the present invention, if the target area trajectory optimization mapping relationship is not matched based on the degree of deviation, the third step size may be updated to the fourth step size in the process of determining the plurality of first target area trajectory mapping relationships, and the operation of determining the target area trajectory optimization mapping relationship from the plurality of first target area trajectory mapping relationships as the second target area trajectory mapping relationship may be repeatedly performed based on the fourth step size. And if the target area track optimization mapping relation can be determined from the plurality of first target area track mapping relations based on the fourth step length, taking the target area track optimization mapping relation as a second target area track mapping relation. It should be noted that the process of determining the target area track optimization mapping relationship from the multiple first target area track mapping relationships as the second target area track mapping relationship based on the fourth step length is similar to the process of determining the target area track optimization mapping relationship from the multiple first target area track mapping relationships as the second target area track mapping relationship based on the third step length, and details are not repeated here.
According to an embodiment of the present invention, a plurality of fourth steps may be set for performing multiple rounds of optimization. For example, in the case that the mapping relation is not optimized by using a fourth step length to match the target area trajectory, another fourth step length may be used for optimization; and repeating the operation until one target area track optimization mapping relation is determined to be used as a second target area track mapping relation, or the target area track optimization mapping relation does not exist.
According to an embodiment of the present invention, the degree of deviation may be variance, difference, deviation, standard deviation, etc., which is not limited by the present invention.
It should be noted that the third threshold, the fourth threshold, the third step size, and the fourth step size described above may be set according to actual needs, and the present invention is not limited to this.
In the embodiment of the invention, the second target area track mapping relation corresponding to the target area is determined from the first target area track mapping relations based on the first target sub-area track mapping relations, so that the optimal track estimation aiming at the target area is obtained, the accurate estimation and compensation of the slant-distance error in the imaging time corresponding to the target area can be ensured, and the quality of the satellite-borne SAR image in the imaging time range of the target area is improved.
In order to make the technical solutions of the present invention more clearly understood by those skilled in the art, the advantages of the present invention will be described below with reference to specific embodiments.
In the embodiment of the invention, the main radar parameters of the simulation experiment are shown in table 1. As shown in table 1, the main radar parameters of the simulation experiment include carrier frequency, modulation frequency, sampling frequency, pulse width, pulse repetition frequency, squint angle, and synthetic aperture time. Wherein the carrier frequency is 9.6GHz, and the modulation frequency is 1.1 × 10 13 Hz/s, sampling frequency of 133333333Hz, pulse widthDegree of 9.24μsThe pulse repetition frequency was 4567Hz, the squint angle was 0 ℃, and the synthetic aperture time was about 1s.
TABLE 1
Fig. 6A and 6B are simulation experiment results before the method of the present invention is used to improve the image quality of the target sub-region. It should be noted that, for simplicity of description, the target sub-region is referred to as a point target hereinafter, and details of this will not be described later.
Fig. 6A is the result of imaging of a point object before processing using the method of the present invention. As shown in fig. 6A, the imaged image of the point target is significantly defocused in the azimuth direction due to the influence of the satellite trajectory error.
Fig. 6B is a sectional view of the point target azimuth corresponding to fig. 6A. As can be seen from the sectional view of the point target in the azimuth direction shown in fig. 6B, due to the influence of the satellite trajectory error, the main lobe and the side lobe are severely aliased and cannot be resolved, which affects the resolution of the point target in the azimuth direction.
Fig. 7 and fig. 8A to 8D are simulation experiment results of the improvement processing of the imaging image quality of the point target by the method of the present invention, respectively.
In the process of improving the quality of the point target imaging image by using the method, errors vertical to the course are added to the satellite track points. Selecting track points of 5 azimuth moments in point target imaging time, and determining 4 first reference track points associated with the track points for each of the 5 track points. Obtaining 5 according to the 5 track points and the corresponding 20 first reference track points 5 And combining the first track points. Then, use 5 5 The first track point combination determines a first target sub-region track mapping relation, and imaging processing is carried out on the basis of the first target sub-region track mapping relation and satellite-borne SAR echo data corresponding to the point target, so that an imaging result of the point target is obtained.
In the embodiment of the invention, the water is respectively collectedOptimizing with different step size strategy to increase imaging contrast by less than 10 -2 As a stopping condition, a first target sub-region track mapping relationship corresponding to the point target is found, and the point target is imaged based on the first target sub-region track mapping relationship, so as to obtain imaging results shown in fig. 7 and fig. 8A to 8D. Fig. 7 shows the imaging result in which the initial step size is 1m, each iteration is reduced by 0.2m, and the imaging result is stopped after 2 iterations (hereinafter referred to as the first step size strategy). Fig. 8A to 8D show the imaging results with a fixed step size of 0.2m, and stopping after 8 iterations (hereinafter referred to as a second step size strategy).
Referring to fig. 6A, fig. 6B and fig. 7 together, compared with the imaging result of the point target before being processed by the method of the present invention, the imaging result obtained by the first step of the growing strategy can significantly improve the defocusing problem of the point target in the azimuth direction, and the focusing degree of the point target is well improved. In addition, the method can clearly distinguish the main lobe from the side lobe, and improves the resolution of the point target in the azimuth direction. Therefore, the quality of the satellite-borne SAR image is improved.
Similarly, as can be seen by comparing fig. 6A with fig. 8A and 8B, the imaging result obtained with the second step strategy can also significantly improve the defocusing problem of the point target in the azimuth direction, and the degree of focusing of the point target is well improved. In addition, as can be seen by comparing fig. 6B with fig. 8C and fig. 8D, the main lobe and the side lobes can be clearly distinguished by using the method of the present invention, and the resolution of the point target in the azimuth direction is improved. Therefore, the quality of the satellite-borne SAR image is improved.
In the embodiment of the present invention, the results of improving the quality of the point target imaging image by using the two step size strategies are also compared, and the comparison result is shown in table 2.
TABLE 2
In the embodiment of the invention, the condition of improving the imaging image quality of the point target can be evaluated by using the peak side lobe ratio, the integral side lobe ratio and the imaging contrast. As shown in Table 2, the peak-to-side lobe ratio and the integrated side lobe ratio obtained by the first step of the length strategy processing were-13.255 dB and-9.79 dB, respectively, and the peak-to-side lobe ratio and the integrated side lobe ratio obtained by the second step of the length strategy processing were-13.258 dB and-9.79 dB, respectively. It can be understood that the peak-to-side lobe ratio obtained by the first step size strategy and the second step size strategy is close to-13.26 dB, and the integral-to-side lobe ratio is close to-10 dB, so that the requirement of image focusing can be met. In addition, the peak-to-side lobe ratio, the integral-to-side lobe ratio and the imaging contrast obtained by the first step of the growing strategy processing are better consistent with the peak-to-side lobe ratio, the integral-to-side lobe ratio and the imaging contrast obtained by the second step of the growing strategy processing, which are consistent with the imaging results shown in fig. 7 and 8A to 8D.
In some embodiments, the method of the present invention may also be utilized to provide image quality improvements for multiple point targets within a target region. This will be described in detail with reference to specific examples.
Figure 9 is the result of imaging of a point object within the target area prior to processing using the method of the present invention.
As shown in fig. 9, the target region includes 5 point targets, such as a point target a, a point target B, a point target C, a point target D, and a point target E. The targets of all the points are influenced by satellite track errors, and all the targets have defocusing in the azimuth direction.
In order to improve the imaging quality of each point target in the target area, the method of the present invention is used for track optimization, so that the optimal track estimation (namely, the track mapping relation of the first target sub-area) under each point target condition can be obtained, and the corresponding imaging quality improvement condition of each target is shown in table 3. As shown in Table 3, the peak sidelobe ratio corresponding to each point target is basically close to-13.26 dB, and the integral sidelobe ratio is basically close to-10 dB, so that the image focusing requirement can be met, and the focusing degree of each point target in the target area can be well improved.
TABLE 3
It can be understood that the optimal track estimation result corresponding to each point target represents the estimation result closest to the actual track in the synthetic aperture time of the corresponding point target. According to the method, the track points of the satellite corresponding to 3 azimuth moments can be selected for each point target within the synthetic aperture time, and the first slope distance under the corresponding optimal estimated track is calculated, so that the first slope distances under 15 azimuth moments are obtained.
Next, based on the 15 azimuth moments and the first slant range of the corresponding point target, trajectory points at the corresponding 15 azimuth moments are selected within the imaging time of the target area, and the minimum slant range error is used as an optimization condition to obtain an optimal trajectory estimation (i.e., a second target area trajectory mapping relationship) for the target area through fitting. And the imaging quality improvement is performed on each point target in the target area by using the optimal trajectory estimation of the target area, resulting in the results shown in table 4 and fig. 10A to 10E.
TABLE 4
Table 4 shows the result of improving the imaging quality of each point target in the target area by using the optimal trajectory estimation of the target area. Fig. 10A to 10E are results of improvement in imaging quality of each point target by the optimal trajectory estimation of the target region.
As shown in table 4 and fig. 10A to 10E, the imaging quality of each point target in the target area is improved by using the optimal trajectory estimation of the target area, so that the focusing effect of each point target can be obviously improved. Moreover, as can be seen from comparing table 3 and table 4, the result of improving the imaging quality of each point target by using the optimal trajectory estimation of the target region has better consistency with the result of improving the imaging quality of each point target by using the optimal trajectory estimation corresponding to each point target.
Based on the method for acquiring the satellite-borne SAR image, the invention also provides a device for acquiring the satellite-borne SAR image.
Fig. 11 schematically shows a block diagram of a space-borne SAR image acquisition device according to an embodiment of the invention.
As shown in fig. 11, in an embodiment of the present invention, the on-board SAR image acquisition apparatus 1100 may include an acquisition module 1110, a first mapping module 1120, a second mapping module 1130, a determination module 1140, and an imaging module 1150.
The obtaining module 1110 is configured to obtain spaceborne SAR echo data for a target region, where the target region includes N target A target sub-region, N target Is an integer of 3 or more.
The first mapping module 1120 is for N target Each target sub-area in each target sub-area is determined within the imaging time of the target sub-area according to the satellite-borne SAR echo data 1 The track points of the satellite corresponding to each azimuth moment are determined according to N 1 Determining a first target sub-region track mapping relation corresponding to the target sub-region by using the individual track points and the satellite track model, N 1 Is an integer of 3 or more.
The second mapping module 1130 is configured to determine N within an imaging time of the target region from the satellite-borne SAR echo data 2 The track points of the satellite corresponding to each azimuth moment are determined according to N 2 A plurality of track points and a satellite track model, determining a plurality of first target area track mapping relations corresponding to the target area, N 2 Is an integer of 5 or more.
The determining module 1140 is for determining according to N target And determining a second target area track mapping relation corresponding to the target area according to the first target sub-area track mapping relation and the plurality of first target area track mapping relations.
The imaging module 1150 is configured to determine a satellite-borne SAR image for the target region according to the second target region trajectory mapping relationship and the satellite-borne SAR echo data for the target region.
It should be noted that the implementation, solved technical problems, implemented functions, and achieved technical effects of each module/unit/subunit and the like in the apparatus part embodiment are respectively the same as or similar to the implementation, solved technical problems, implemented functions, and achieved technical effects of each corresponding step in the method part embodiment, and are not described herein again.
According to an embodiment of the present invention, any plurality of the obtaining module 1110, the first mapping module 1120, the second mapping module 1130, the determining module 1140 and the imaging module 1150 may be combined and implemented in one module, or any one of them may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in one module. According to an embodiment of the present invention, at least one of the obtaining module 1110, the first mapping module 1120, the second mapping module 1130, the determining module 1140 and the imaging module 1150 may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or implemented by any one of three implementations of software, hardware and firmware, or any suitable combination of any of them. Alternatively, at least one of the acquisition module 1110, the first mapping module 1120, the second mapping module 1130, the determination module 1140 and the imaging module 1150 may be at least partially implemented as a computer program module, which when executed, may perform corresponding functions.
The invention also provides an electronic device, a readable storage medium and a computer program product according to the embodiments of the invention.
According to an embodiment of the present invention, an electronic apparatus includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method as described above.
According to an embodiment of the present invention, a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to execute the method as described above.
According to an embodiment of the invention, a computer program product comprises a computer program which, when executed by a processor, implements the method as described above.
Fig. 12 schematically shows a block diagram of an electronic device suitable for implementing the method for acquiring a SAR image on board, according to an embodiment of the invention.
As shown in fig. 12, an electronic apparatus 1200 according to an embodiment of the present invention includes a processor 1201 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 1202 or a program loaded from a storage section 1208 into a Random Access Memory (RAM) 1203. The processor 1201 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 1201 may also include on-board memory for caching purposes. The processor 1201 may include a single processing unit or a plurality of processing units for performing the different actions of the method flows according to embodiments of the present invention.
In the RAM 1203, various programs and data necessary for the operation of the electronic apparatus 1200 are stored. The processor 1201, the ROM 1202, and the RAM 1203 are connected to each other by a bus 1204. The processor 1201 performs various operations of the method flow according to the embodiment of the present invention by executing programs in the ROM 1202 and/or the RAM 1203. Note that the programs may also be stored in one or more memories other than the ROM 1202 and the RAM 1203. The processor 1201 may also perform various operations of method flows according to embodiments of the present invention by executing programs stored in the one or more memories.
The present invention also provides a computer-readable storage medium, which may be embodied in the device/apparatus/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the present invention.
According to embodiments of the present invention, the computer readable storage medium may be a non-volatile computer readable storage medium, which may include, for example but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the invention, a computer-readable storage medium may include the ROM 1202 and/or the RAM 1203 and/or one or more memories other than the ROM 1202 and the RAM 1203 described above.
Embodiments of the invention also include a computer program product comprising a computer program comprising program code for performing the method illustrated in the flow chart. When the computer program product runs in a computer system, the program code is used for causing the computer system to realize the on-board SAR image acquisition method provided by the embodiment of the invention.
The computer program performs the above-described functions defined in the system/apparatus of the embodiment of the present invention when executed by the processor 1201. The above described systems, devices, modules, units, etc. may be implemented by computer program modules according to embodiments of the invention.
In one embodiment, the computer program may be hosted on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted, distributed in the form of a signal on a network medium, downloaded and installed through the communication section 1209, and/or installed from the removable medium 1211. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 1209, and/or installed from the removable medium 1211. The computer program, when executed by the processor 1201, performs the above-described functions defined in the system of the embodiment of the present invention. The above described systems, devices, apparatuses, modules, units, etc. may be implemented by computer program modules according to embodiments of the present invention.
According to embodiments of the present invention, program code for executing a computer program provided by embodiments of the present invention may be written in any combination of one or more programming languages, and in particular, the computer program may be implemented using a high level procedural and/or object oriented programming language, and/or an assembly/machine language. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
It will be appreciated by a person skilled in the art that features described in the various embodiments of the invention may be combined and/or coupled in a number of ways, even if such combinations or couplings are not explicitly described in the invention. In particular, the features recited in the various embodiments of the present invention may be combined and/or coupled in various ways without departing from the spirit and teachings of the invention. All such combinations and/or associations are within the scope of the present invention.
The embodiments of the present invention have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the invention, and these alternatives and modifications are intended to fall within the scope of the invention.
Claims (12)
1. A satellite-borne SAR image acquisition method is characterized by comprising the following steps:
acquiring satellite-borne SAR echo data for a target region, wherein the target region comprises N target A target sub-region, N target Is an integer of 3 or more;
for N target Determining N target sub-regions in the imaging time of each target sub-region according to the satellite-borne SAR echo data 1 The track points of the satellite corresponding to each azimuth moment are determined according to N 1 Determining a first target sub-region track mapping relation corresponding to the target sub-region by using the track points and the satellite track model, N 1 Is an integer of 3 or more;
determining N within the imaging time of the target area according to the satellite-borne SAR echo data 2 The track points of the satellite corresponding to each azimuth moment are determined according to N 2 Determining a plurality of first target area track mapping relations corresponding to the target areas by the track points and the satellite track model, N 2 Is an integer of 5 or more;
according to N target Determining a second target area track mapping relation corresponding to the target area according to the first target sub-area track mapping relation and the first target area track mapping relations;
determining a satellite-borne SAR image aiming at the target area according to the second target area track mapping relation and the satellite-borne SAR echo data aiming at the target area;
said according to N target Determining a second target area track mapping relationship corresponding to the target area, wherein the first target area track mapping relationship and the second target area track mapping relationship comprise:
for N target A first target sub-regionEach of the trajectory mapping relationships is determined with N during an imaging time of the target sub-region orb The track points of the satellite corresponding to the azimuth time are determined respectively based on the track mapping relation of the first target sub-area orb The slant distance between each track point and the central target point of the target sub-area is obtained to obtain N orb A first pitch; n is a radical of hydrogen orb Is an integer of 3 or more;
for each of a plurality of first target area trajectory mapping relationships, determining N based on the first target area trajectory mapping relationship target N corresponding to each target sub-region in each target sub-region orb The slope distance at each azimuth moment is obtained as N target *N orb A second slope distance is set between the first slope distance and the second slope distance,
determining the N for each of a plurality of first target area trajectory mapping relationships target *N orb A second slope distance and N target N of track mapping relation of first target sub-regions orb A degree of deviation between the first slope distances; and
and determining a target area track optimization mapping relation from a plurality of first target area track mapping relations as the second target area track mapping relation based on the deviation degree.
2. The method of claim 1, wherein the method is based on N 1 Determining a first target sub-region track mapping relation corresponding to the target sub-region by using the track points and the satellite track model, wherein the first target sub-region track mapping relation comprises:
for N 1 Each track point in the track points determines a plurality of first reference track points associated with the track point according to the track point and the first step length;
according to N 1 A track point and N 1 A plurality of first reference track points which are respectively associated with the plurality of track points are obtained to obtain a plurality of first track point combinations;
determining a plurality of second target sub-region track mapping relations corresponding to the target sub-regions according to the plurality of first track point combinations and the satellite track model; and
and determining a target sub-region track optimization mapping relation from the plurality of second target sub-region track mapping relations as the first target sub-region track mapping relation.
3. The method of claim 2, wherein the function N is 1 Determining a first target sub-region track mapping relationship corresponding to the target sub-region by using the track points and the satellite track model, and further comprising:
in response to not matching the target sub-region track optimization mapping relationship from among the plurality of second target sub-region track mapping relationships, updating the first step size to a second step size; and
and based on the second step size, repeatedly executing the operation of determining a target sub-region track optimization mapping relation from the plurality of second target sub-region track mapping relations as the first target sub-region track mapping relation.
4. The method of claim 2 or 3, wherein determining a target sub-region trajectory optimization mapping from the plurality of second target sub-region trajectory mappings comprises:
respectively using the plurality of second target sub-region track mapping relations and satellite-borne SAR echo data corresponding to the target sub-regions to perform imaging processing on the target sub-regions to obtain a plurality of complex image data;
obtaining a plurality of imaging contrasts according to the plurality of complex image data; and
responding to the trigger of a preset condition, and taking a second target sub-region track mapping relation corresponding to the maximum imaging contrast in the multiple imaging contrasts as the target sub-region track optimization mapping relation.
5. The method of claim 4, wherein the preset condition comprises at least one of:
the increment of the maximum imaging contrast obtained by the optimization relative to the maximum imaging contrast obtained by the previous optimization is less than or equal to a first threshold; and
the step length corresponding to the optimization is less than or equal to a second threshold value.
6. The method of claim 1, wherein the method is based on N 2 Determining a plurality of first target area track mapping relationships corresponding to the target area, including:
for N 2 Determining a plurality of second reference track points associated with each track point according to the track point and the third step length;
according to N 2 A track point and N 2 The plurality of track points are respectively associated with a plurality of second reference track points to obtain a plurality of second track point combinations; and
and determining a plurality of first target area track mapping relations corresponding to the target area according to the plurality of second track point combinations and the satellite track model.
7. The method of claim 6, wherein the function N is target Determining a second target area trajectory mapping relationship corresponding to the target area further includes:
in response to not matching the target region trajectory optimization mapping from the plurality of first target region trajectory mapping relationships to the target region trajectory optimization mapping relationship based on the degree of deviation, updating the third step size to a fourth step size; and
based on the fourth step size, repeatedly executing the operation of determining the target area track optimization mapping relation from the plurality of first target area track mapping relations as the second target area track mapping relation.
8. The method according to claim 1, 6 or 7, wherein the determining a target area trajectory optimization mapping relationship from a plurality of first target area trajectory mapping relationships as the second target area trajectory mapping relationship based on the degree of deviation comprises:
determining a minimum degree of deviation from a plurality of degrees of deviation; and
and determining a first target area track mapping relation corresponding to the minimum deviation degree as the target area track optimization mapping relation in response to the minimum deviation degree being smaller than or equal to a third threshold value.
9. The method of claim 7, wherein determining a target region trajectory optimization mapping from a plurality of first target region trajectory mapping relationships as the second target region trajectory mapping relationship based on the degree of deviation comprises:
determining a minimum degree of deviation from the plurality of degrees of deviation; and
and determining the first target area track mapping relation corresponding to the minimum deviation degree as the target area track optimization mapping relation in response to that the step length corresponding to the optimization is smaller than or equal to a fourth threshold value.
10. A satellite-borne SAR image acquisition device is characterized by comprising:
an acquisition module for acquiring spaceborne SAR echo data for a target region, wherein the target region comprises N target A target sub-region, N target Is an integer of 3 or more;
a first mapping module for mapping N target Determining N target sub-regions in the imaging time of each target sub-region according to the satellite-borne SAR echo data 1 The track points of the satellite corresponding to each azimuth moment are determined according to N 1 Determining a first target sub-region track mapping relation corresponding to the target sub-region by using the track points and the satellite track model, N 1 Is an integer of 3 or more;
a second mapping module for imaging the target region within the imaging time according to the satellite-borne SAR echo dataDetermining the sum of N 2 The track points of the satellite corresponding to each azimuth moment are determined according to N 2 Determining a plurality of first target area track mapping relations corresponding to the target areas by the track points and the satellite track model, N 2 Is an integer of 5 or more;
a determination module for determining according to N target Determining a second target area track mapping relation corresponding to the target area according to the first target sub-area track mapping relation and the first target area track mapping relations;
the imaging module is used for determining a satellite-borne SAR image aiming at the target area according to the second target area track mapping relation and the satellite-borne SAR echo data aiming at the target area;
the determination module is further to:
for N target Each of a first target sub-region trajectory mapping relationship is determined with N within an imaging time of the target sub-region orb The track points of the satellite corresponding to the azimuth time are determined respectively based on the track mapping relation of the first target sub-area orb The slant distance between each track point and the central target point of the target sub-area is obtained to obtain N orb A first pitch; n is a radical of hydrogen orb Is an integer of 3 or more;
determining N for each of a plurality of first target area trajectory mappings based on the first target area trajectory mapping target N corresponding to each target sub-region in each target sub-region orb The slope distance at each azimuth moment is obtained as N target *N orb A second slope distance is set between the first slope distance and the second slope distance,
determining the N for each of a plurality of first target area trajectory mapping relationships target *N orb A second slope distance and N target N of track mapping relation of first target sub-regions orb A degree of deviation between the first slope distances; and
and determining a target area track optimization mapping relation from a plurality of first target area track mapping relations as the second target area track mapping relation based on the deviation degree.
11. An electronic device, comprising:
one or more processors;
a memory for storing one or more programs,
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of any of claims 1 to 9.
12. A computer-readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 9.
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Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2014012828A1 (en) * | 2012-07-19 | 2014-01-23 | Deutsches Zentrum für Luft- und Raumfahrt e.V. | Method for processing high-resolution spaceborne spotlight sar raw data |
CN106556822A (en) * | 2016-11-09 | 2017-04-05 | 上海卫星工程研究所 | Spaceborne Sliding spotlight SAR pointing accuracy Orbital detection method |
CN106886021A (en) * | 2017-01-24 | 2017-06-23 | 上海卫星工程研究所 | High Resolution Spaceborne SAR image quality method for improving |
CN110488294A (en) * | 2019-09-09 | 2019-11-22 | 上海无线电设备研究所 | A kind of spaceborne more baseline holography SAR imaging methods |
CN111381217A (en) * | 2020-04-01 | 2020-07-07 | 上海无线电设备研究所 | Missile-borne SAR motion compensation method based on low-precision inertial navigation system |
CN113640794A (en) * | 2021-07-20 | 2021-11-12 | 北京理工大学 | MIMO-SAR three-dimensional imaging self-focusing method |
CN114384519A (en) * | 2022-03-23 | 2022-04-22 | 中国科学院空天信息创新研究院 | Ultrahigh resolution spaceborne synthetic aperture radar imaging method and device |
CN114910911A (en) * | 2022-07-18 | 2022-08-16 | 中国科学院空天信息创新研究院 | Satellite-borne multi-base SAR imaging method based on multi-phase center reconstruction |
CN115128603A (en) * | 2022-06-17 | 2022-09-30 | 北京理工大学 | Satellite-borne SAR non-tracking multi-target imaging satellite-ground configuration joint design and optimization method |
-
2022
- 2022-10-08 CN CN202211219052.9A patent/CN115291216B/en active Active
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2014012828A1 (en) * | 2012-07-19 | 2014-01-23 | Deutsches Zentrum für Luft- und Raumfahrt e.V. | Method for processing high-resolution spaceborne spotlight sar raw data |
CN106556822A (en) * | 2016-11-09 | 2017-04-05 | 上海卫星工程研究所 | Spaceborne Sliding spotlight SAR pointing accuracy Orbital detection method |
CN106886021A (en) * | 2017-01-24 | 2017-06-23 | 上海卫星工程研究所 | High Resolution Spaceborne SAR image quality method for improving |
CN110488294A (en) * | 2019-09-09 | 2019-11-22 | 上海无线电设备研究所 | A kind of spaceborne more baseline holography SAR imaging methods |
CN111381217A (en) * | 2020-04-01 | 2020-07-07 | 上海无线电设备研究所 | Missile-borne SAR motion compensation method based on low-precision inertial navigation system |
CN113640794A (en) * | 2021-07-20 | 2021-11-12 | 北京理工大学 | MIMO-SAR three-dimensional imaging self-focusing method |
CN114384519A (en) * | 2022-03-23 | 2022-04-22 | 中国科学院空天信息创新研究院 | Ultrahigh resolution spaceborne synthetic aperture radar imaging method and device |
CN115128603A (en) * | 2022-06-17 | 2022-09-30 | 北京理工大学 | Satellite-borne SAR non-tracking multi-target imaging satellite-ground configuration joint design and optimization method |
CN114910911A (en) * | 2022-07-18 | 2022-08-16 | 中国科学院空天信息创新研究院 | Satellite-borne multi-base SAR imaging method based on multi-phase center reconstruction |
Non-Patent Citations (3)
Title |
---|
A New Geosynchronous SAR Constellation and Its Signal Characteristics;Xu Hailong, et al.;《IEEE Access》;20190809;第7卷;第101540-101550页 * |
同步轨道SAR参数分析及成像方法;李军等;《系统工程与电子技术》;20100515;第32卷(第05期);第932-935页 * |
考虑运动补偿的机载SAR定位误差传递模型及航迹标定方法;高铭等;《雷达学报》;20210831;第10卷(第4期);第647-652页 * |
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